This paper describes a state of charge (SoC) indication method for the battery system of an electric vehicle "Green Jumper", which has been developed in National Taiwan University. In this new SoC indication method, power loss computing algorithm, Coulomb counting and EMF-versus-SoC curve methods are combined to improve the accuracy. The core idea of this method is the power loss computing algorithm, which is calculated from battery equivalent internal resistance. Because the equivalent internal resistance of the battery cell varies from status and environment, thus it is designed in the proposed algorithm to be computed from its overpotential behavior in different charge or discharge states. The SoC indication method in this paper corrects Coulomb counting method by calculating the power loss value and hence the accuracy of SoC indication can be improved. The algorithm has been installed in a battery managing system and tests have shown that the performance is in good agreement with the design target. The algorithm will be installed in a battery managing system for Green Jumper EV for on road test.
Computing battery SoC by real-time internal resistance determination
2010
7 Seiten, 13 Bilder, 5 Tabellen, 9 Quellen
(nicht paginiert)
Aufsatz (Konferenz)
Datenträger
Englisch
INTELLIGENT BATTERY SENSOR AND BATTERY INTERNAL RESISTANCE ESTIMATION METHOD THEREOF
Europäisches Patentamt | 2019
|BATTERY STATE DIAGNOSTIC DEVICE, AND BATTERY INTERNAL RESISTANCE MEASUREMENT METHOD
Europäisches Patentamt | 2015
|BATTERY STATE DIAGNOSING DEVICE, AND BATTERY INTERNAL RESISTANCE MEASURING METHOD
Europäisches Patentamt | 2015
|INTELLIGENT BATTERY SENSOR AND BATTERY INTERNAL RESISTANCE ESTIMATION METHOD THEREOF
Europäisches Patentamt | 2023
Real-time estimation of battery internal temperature based on a simplified thermoelectric model
Online Contents | 2016
|